Supply of, and demand for, a resource: Fuzzy logistical optimisation technique
AbstractFuzzy logistical analysis for exploiting a resource helps determine the relative strengths and weaknesses of various supply-demand chains linking alternative sources (in the supply sector) to their final points of use (in the demand sector). There are benefits and constraints associated with each supply and demand sector. Fuzzy theory is applied to the logistical optimisation of these sectors in order to assess the relative importance or degree of association between the supply and demand determinants, which therefore should influence the decisions made for the exploitation strategies adopted for different sectors. Each supply determinant is related to each demand determinant. From their relative values of association, the relationship corresponding to each supply-demand pathway can be calculated and compared with those for the remaining pathways. Such information is valuable, for example when devising and implementing strategies affecting waste management and the recycling of materials and/or energy.
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Bibliographic InfoArticle provided by Elsevier in its journal Applied Energy.
Volume (Year): 46 (1993)
Issue (Month): 4 ()
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description
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- Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
- Kucukali, Serhat & Baris, Kemal, 2010. "Turkey's short-term gross annual electricity demand forecast by fuzzy logic approach," Energy Policy, Elsevier, vol. 38(5), pages 2438-2445, May.
- Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, Open Access Journal, vol. 4(10), pages 1624-1656, October.
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